Abstract
Introduction: Current research suggests that self-selected walking speed is an important indicator of hemiparetic gait rehabilitation outcome and can be targeted for improvement. Analysis of the relationship between walking speed and the kinematic profiles of the hemiparetic gait cycle can be expanded by comparing variations in their time dependant waveforms.
Methods: This paper is a pilot study to explore utilising the Linear Fit Method to compare the gait of a group of stroke survivors against a healthy baseline with respect to walking speed. This produced a set of parameters with clear physiological meaning that describe the variation of the hemiparetic gait pattern from the healthy pattern. A linear regression analysis was then performed comparing the resulting parameters against gait speed.
Results: Significant linear relationships (p < 0.05) were found between the Linear Fit parameters describing the hemiparetic gait pattern variations and walking speed in both paretic and non-paretic limbs. Most notably peak paretic knee flexion reduced by 20° and peak paretic hip abductions reducing to a nearly normal pattern while peak paretic hip flexions increased by 10°. The non-paretic hip flexion peak extensions remained 10° below the healthy comparison hip abduction offset was reduced but remained at nearly 2.5° to 5° from the healthy comparison.
Conclusions: As stroke survivors achieved higher walking speeds some aspects of their gait became more similar to the healthy comparison though others had no relation, or their differences became more pronounced. Combined, these relations show how paretic and non-paretic joint kinematics can be used to start identifying and quantifying effective compensatory hemiparetic gait patterns.
Methods: This paper is a pilot study to explore utilising the Linear Fit Method to compare the gait of a group of stroke survivors against a healthy baseline with respect to walking speed. This produced a set of parameters with clear physiological meaning that describe the variation of the hemiparetic gait pattern from the healthy pattern. A linear regression analysis was then performed comparing the resulting parameters against gait speed.
Results: Significant linear relationships (p < 0.05) were found between the Linear Fit parameters describing the hemiparetic gait pattern variations and walking speed in both paretic and non-paretic limbs. Most notably peak paretic knee flexion reduced by 20° and peak paretic hip abductions reducing to a nearly normal pattern while peak paretic hip flexions increased by 10°. The non-paretic hip flexion peak extensions remained 10° below the healthy comparison hip abduction offset was reduced but remained at nearly 2.5° to 5° from the healthy comparison.
Conclusions: As stroke survivors achieved higher walking speeds some aspects of their gait became more similar to the healthy comparison though others had no relation, or their differences became more pronounced. Combined, these relations show how paretic and non-paretic joint kinematics can be used to start identifying and quantifying effective compensatory hemiparetic gait patterns.
Original language | English |
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Article number | 100733 |
Number of pages | 11 |
Journal | IRBM |
Volume | 44 |
Issue number | 1 |
Early online date | 5 Sept 2022 |
DOIs | |
Publication status | Published - Feb 2023 |
Bibliographical note
Funding Information:The authors thank the West Midlands Rehabilitation Centre, part of the Birmingham Community Healthcare NHS Foundation Trust for their support in the data collection used in this study.
Publisher Copyright:
© 2022 AGBM
Keywords
- Gait analysis
- Hemiparetic gait
- Stroke
- Gait rehabilitation
- Linear fit method
ASJC Scopus subject areas
- Biophysics
- Biomedical Engineering